Dimethyl Sulfoxide Damages Mitochondrial Integrity and Membrane Potential in Cultured Astrocytes

Dimethyl sulfoxide (DMSO) is a polar organic solvent that is used to dissolve neuroprotective or neurotoxic agents in neuroscience research. However, DMSO itself also has pharmacological and pathological effects on the nervous system. Astrocytes play a central role in maintaining brain homeostasis, but the effect and mechanism of DMSO on astrocytes has not been studied. The present study showed that exposure of astrocyte cultures to 1% DMSO for 24 h did not significantly affect cell survival, but decreased cell viability and glial glutamate transporter expression, and caused mitochondrial swelling, membrane potential impairment and reactive oxygen species production, and subsequent cytochrome c release and caspase-3 activation. DMSO at concentrations of 5% significantly inhibited cell variability and promoted apoptosis of astrocytes, accompanied with more severe mitochondrial damage. These results suggest that mitochondrial impairment is a primary event in DMSO-induced astrocyte toxicity. The potential cytotoxic effects on astrocytes need to be carefully considered during investigating neuroprotective or neurotoxic effects of hydrophobic agents dissolved by DMSO

Saikosaponin A Alleviates Symptoms of Attention Deficit Hyperactivity Disorder through Downregulation of DAT and Enhancing BDNF Expression in Spontaneous Hypertensive Rats

The disturbed dopamine availability and brain-derived neurotrophic factor (BDNF) expression are due in part to be associated with attention deficit hyperactivity disorder (ADHD). In this study, we investigated the therapeutical effect of saikosaponin a (SSa) isolated from Bupleurum Chinese DC, against spontaneously hypertensive rat (SHR) model of ADHD. Methylphenidate and SSa were orally administered for 3 weeks. Activity was assessed by open-field test and Morris water maze test. Dopamine (DA) and BDNF were determined in specific brain regions. The mRNA or protein expression of tyrosine hydroxylase (TH), dopamine transporter (DAT), and vesicles monoamine transporter (VMAT) was also studied. Both MPH and SSa reduced hyperactivity and improved the spatial learning memory deficit in SHRs. An increased DA concentration in the prefrontal cortex (PFC) and striatum was also observed after treating with the SSa. The increased DA concentration may partially be attributed to the decreased mRNA and protein expression of DAT in PFC while SSa exhibited no significant effects on the mRNA expression of TH and VMAT in PFC of SHRs. In addition, BDNF expression in SHRs was also increased after treating with SSa or MPH. The obtained result suggested that SSa may be a potential drug for treating ADHD

Research on Comprehensive Evaluation Method of Airport Runway Operational Effectiveness

In order to assess whether the runway can meet safe, reliable and efficient objectives, a comprehensive evaluation indicator system needs to be established for evaluation. Firstly, the runway operation system is established, and the evaluation indicators of runway performance are divided into five aspects: personnel factors, support facility, mission demand, operating environment and management factors and then establish a comprehensive evaluation index system. Secondly, the TOPSIS evaluation model of game theory combination weighting is established, game theory is used to optimize the weights of the weights obtained by AHP and CRITIC, and the ideal solution (TOPSIS) is used to comprehensively evaluate the runway performance. Finally, the model was used to evaluate the runway performance levels of the three airports, and the three evaluation methods were compared. The results show that the results of the runway performance evaluation using the model are in line with the actual operation of the airport. The method is simple and the results are scientific and objective, and it have good versatility

A Novel Link Prediction Method for Social Multiplex Networks Based on Deep Learning

Due to the great advances in information technology, an increasing number of social platforms have appeared. Friend recommendation is an important task in social media, but newly built social platforms have insufficient information to predict entity relationships. In this case, platforms with sufficient information can help newly built platforms. To address this challenge, a model of link prediction in social multiplex networks (LPSMN) is proposed in this work. Specifically, we first extract graph structure features, latent features and explicit features and then concatenate these features as link representations. Then, with the assistance of external information from a mature platform, an attention mechanism is employed to construct a multiplex and enhanced forecasting model. Additionally, we consider the problem of link prediction to be a binary classification problem. This method utilises three different kinds of features to improve link prediction performance. Finally, we use five synthetic networks with various degree distributions and two real-world social multiplex networks (Weibo–Douban and Facebook–Twitter) to build an experimental scenario for further assessment. The numerical results indicate that the proposed LPSMN model improves the prediction accuracy compared with several baseline methods. We also find that with the decline in network heterogeneity, the performance of LPSMN increases

Chinese striped-neck turtles vocalize underwater and show differences in peak frequency among different age and sex groups

Background Turtle vocalizations play an important role throughout their lives by expressing individual information (position, emotion, or physiological status), reflecting mating preferences, and synchronizing incubation. The Chinese striped-neck turtle (Mauremys sinensis) is one of the most widely distributed freshwater turtles in China, whose wild population is critically endangered. However, its vocalization has not been studied, which can be the basis for behavioral and ecological studies. Methods Five different sex–age groups of turtles were recorded underwater in a soundproof room. Cluster analysis and principal component analysis for classification of Chinese striped-neck turtle calls were unreasonable. The turtle calls were manually sought using visual and aural inspection of the recordings in Raven Pro 1.5 software and classified according to differences perceived through auditory inspection and the morphological characteristics of the spectrograms. The results of similarity analysis verified the reliability of manual classification. We compared the peak frequency of the calls among different age and sex groups. Results We identified ten M. sinensis call types, displayed their spectra and waveforms, and described their auditory characteristics. Most calls produced by the turtles were low-frequency. Some high-frequency call types, that are common in other turtle species were also produced. Similar to other turtles, the Chinese striped-neck turtle generates harmonic vocalizations. Courtship behaviors were observed when one of the call types occurred in the mixed-sex group. Adult females produced more high-frequency call types, and subadult males had higher vocalizations than other groups. These results provide a basis for future research on the function of vocalizations, field monitoring, and conservation of this species

Unstart Coupling Mechanism Analysis of Multiple-Modules Hypersonic Inlet

The combination of multiplemodules in parallel manner is an important way to achieve the much higher thrust of scramjet engine. For the multiple-modules scramjet engine, when inlet unstarted oscillatory flow appears in a single-module engine due to high backpressure, how to interact with each module by massflow spillage, and whether inlet unstart occurs in other modules are important issues. The unstarted flowfield and coupling characteristic for a three-module hypersonic inlet caused by center module II and side module III were, conducted respectively. The results indicate that the other two hypersonic inlets are forced into unstarted flow when unstarted phenomenon appears on a single-module hypersonic inlet due to high backpressure, and the reversed flow in the isolator dominates the formation, expansion, shrinkage, and disappearance of the vortexes, and thus, it is the major factor of unstart coupling of multiple-modules hypersonic inlet. The coupling effect among multiple modules makes hypersonic inlet be more likely unstarted

Application of Machine Learning for Predicting Anastomotic Leakage in Patients with Gastric Adenocarcinoma Who Received Total or Proximal Gastrectomy

Anastomotic leakage is a life-threatening complication in patients with gastric adenocarcinoma who received total or proximal gastrectomy, and there is still no model accurately predicting anastomotic leakage. In this study, we aim to develop a high-performance machine learning tool to predict anastomotic leakage in patients with gastric adenocarcinoma received total or proximal gastrectomy. A total of 1660 cases of gastric adenocarcinoma patients who received total or proximal gastrectomy in a large academic hospital from 1 January 2010 to 31 December 2019 were investigated, and these patients were randomly divided into training and testing sets at a ratio of 8:2. Four machine learning models, such as logistic regression, random forest, support vector machine, and XGBoost, were employed, and 24 clinical preoperative and intraoperative variables were included to develop the predictive model. Regarding the area under the receiver operating characteristic curve (AUC), sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy, random forest had a favorable performance with an AUC of 0.89, a sensitivity of 81.8% and specificity of 82.2% in the testing set. Moreover, we built a web app based on random forest model to achieve real-time predictions for guiding surgeons’ intraoperative decision making

Anisotropic nanostructure generated by a spatial-temporal manipulated picosecond pulse for multidimensional optical data storage

Anisotropic nanostructures can be generated in fused silica glass by manipulating the spatiotemporal properties of a picosecond pulse. This phenomenon is attributed to the laser-induced interband self-trapped excitons. The anisotropic structures exhibit birefringent properties, and thus can be employed for multi-dimensional optical data storage applications. The generation of data voxels by such short laser irradiation enables on-the-fly high-speed data recording

Transcriptome Analyses Provide Insights into the Auditory Function in <i>Trachemys scripta elegans</i>

An auditory ability is essential for communication in vertebrates, and considerable attention has been paid to auditory sensitivity in mammals, birds, and frogs. Turtles were thought to be deaf for a long time; however, recent studies have confirmed the presence of an auditory ability in Trachemys scripta elegans as well as sex-related differences in hearing sensitivity. Earlier studies mainly focused on the morphological and physiological functions of the hearing organ in turtles; thus, the gene expression patterns remain unclear. In this study, 36 transcriptomes from six tissues (inner ear, tympanic membrane, brain, eye, lung, and muscle) were sequenced to explore the gene expression patterns of the hearing system in T. scripta elegans. A weighted gene co-expression network analysis revealed that hub genes related to the inner ear and tympanic membrane are involved in development and signal transduction. Moreover, we identified six differently expressed genes (GABRA1, GABRG2, GABBR2, GNAO1, SLC38A1, and SLC12A5) related to the GABAergic synapse pathway as candidate genes to explain the differences in sexually dimorphic hearing sensitivity. Collectively, this study provides a critical foundation for genetic research on auditory functions in turtles